Virtue ethics has been challenged on empirical grounds by philosophical interpreters of situationist social psychology. Challenges are necessarily challenges to something or other, so it’s only possible to understand the situationist challenge to virtue ethics if we have an antecedent grasp on virtue ethics itself. To this end, I first identify the non-negotiable “hard core” of virtue ethics with the conjunction of nine claims, arguing that virtue ethics does make substantive empirical assumptions about human conduct. Next, I rearticulate the situationist (...) challenge in light of these nine claims. I then turn to a discussion of specifications of several responses typically made by defenders of virtue ethics against the situationist challenge, arguing that most of them either are unsound or give up one of the elements in the hard core. A few, however, survive this criticism, and so I conclude by suggesting ways in which the situationist challenge might be not so much resisted as co-opted. Situational influences can be used to help people simulate virtue, a phenomenon I call factitious virtue. (shrink)

Julian Reiss correctly identified a trilemma about economic models: we cannot maintain that they are false, but nevertheless explain and that only true accounts explain. In this reply we give reasons to reject the second premise ? that economic models explain. Intuitions to the contrary should be distrusted.

How can we think about things in the outside world? There is still no widely accepted theory of how mental representations get their meaning. In light of pioneering research, Nicholas Shea develops a naturalistic account of the nature of mental representation with a firm focus on the subpersonal representations that pervade the cognitive sciences.

People are adept at inferring novel causal relations, even from only a few observations. Prior knowledge about the probability of encountering causal relations of various types and the nature of the mechanisms relating causes and effects plays a crucial role in these inferences. We test a formal account of how this knowledge can be used and acquired, based on analyzing causal induction as Bayesian inference. Five studies explored the predictions of this account with adults and 4-year-olds, using tasks in which (...) participants learned about the causal properties of a set of objects. The studies varied the two factors that our Bayesian approach predicted should be relevant to causal induction: the prior probability with which causal relations exist, and the assumption of a deterministic or a probabilistic relation between cause and effect. Adults’ judgments (Experiments 1, 2, and 4) were in close correspondence with the quantitative predictions of the model, and children’s judgments (Experiments 3 and 5) agreed qualitatively with this account. (shrink)

The Gettier Problem is the problem of revising the view that knowledge is justified true belief in a way that is immune to Gettier counter-examples. The “Gettier Problem problem”, according to Lycan, is the problem of saying what is misguided about trying to solve the Gettier Problem. In this paper I take up the Gettier Problem problem. I distinguish giving conditions that are necessary and sufficient for knowledge from giving conditions that explain why one knows when one does know. I (...) argue that the problem with the Gettier Problem is that it requires us to articulate conditions that suffice for knowledge even if those conditions are non-explanatory. After defending this view, I take up two related methodological issues, one about the evidence that can be given in favor of an account of knowledge, and one about the role that investigating justification might play in investigating knowledge. (shrink)

A crucial question for a process view of life is how to identify a process and how to follow it through time. The genidentity view can contribute decisively to this project. It says that the identity through time of an entity X is given by a well-identified series of continuous states of affairs. Genidentity helps address the problem of diachronic identity in the living world. This chapter describes the centrality of the concept of genidentity for David Hull and proposes an (...) extension of Hull’s view to the ubiquitous phenomenon of symbiosis. Finally, using immunology as a key example, it shows that the genidentity view suggests that the main interest of a process approach is epistemological rather than ontological and that its principal claim is one of priority, namely that processes precede and define things, and not vice versa. (shrink)

Any successful account of the metaphysics of mechanistic causation must satisfy at least five key desiderata. In this article, I lay out these five desiderata and explain why existing accounts of the metaphysics of mechanistic causation fail to satisfy them. I then present an alternative account that does satisfy the five desiderata. According to this alternative account, we must resort to a type of ontological entity that is new to metaphysics, but not to science: constraints. In this article, I explain (...) how a constraints-based metaphysics fits best with the emerging consensus on the nature of mechanistic explanation. 1Introduction2Renormalizability2.1The first two desiderata: Intrinsicness and productivity2.2The third desideratum: Scientific validity or non-mysteriousness2.3The fourth desideratum: Directionality2.4The fifth desideratum: Perspectival nature of mechanisms3Constraints and Causation3.1Multi-perspectival realism and causal structure3.2Causal structure as laws3.3Causal structures in analytical mechanics: Constraints3.4A metaphysics inspired by analytical mechanics: Constraints as ontologically primitive modal structures4Constraints and Mechanistic Causal Powers 4.1Inter- versus intra-perspectival categories4.2Mechanistic causal powers are grounded by constraints4.3Intrinsicness and constraints4.4Constraints and productiveness4.5Constraints and directionality5Conclusion. (shrink)

In the spirit of explanatory pluralism, this chapter argues that causal and noncausal explanations of a phenomenon are compatible, each being useful for bringing out different sorts of insights. After reviewing a model-based account of scientific explanation, which can accommodate causal and noncausal explanations alike, an important core conception of noncausal explanation is identified. This noncausal form of model-based explanation is illustrated using the example of how Earth scientists in a subfield known as aeolian geomorphology are explaining the formation of (...) regularlyspaced sand ripples. The chapter concludes that even when it comes to everyday "medium-sized dry goods" such as sand ripples, where there is a complete causal story to be told, one can find examples of noncausal scientific explanations. (shrink)

Die Einleitung unseres Kapitels bietet eine grundsäzliche Charakterisierung der Soziologie und zeichnet einige wichtige historische Entwicklungslinien der Philosophie der Soziologie (PdS) nach. Im Hauptteil werden zentrale ontologische sowie ausgewählte explanatorische Themen der PdS vorgestellt. Im Schlussteil sollen einige aktuelle Diskussionen umrissen werden.

In this chapter we examine the relation between mechanisms and laws/counterfactuals by revisiting the main notions of mechanism found in the literature. We distinguish between two different conceptions of ‘mechanism’: mechanisms-of underlie or constitute a causal process; mechanisms-for are complex systems that function so as to produce a certain behavior. According to some mechanists, a mechanism fulfills both of these roles simultaneously. The main argument of the chapter is that there is an asymmetrical dependence between both kinds of mechanisms and (...) laws/counterfactuals: while some laws and counterfactuals must be taken as primitive (non-mechanistic) facts of the world, all mechanisms depend on laws/counterfactuals. (shrink)

When scientists seek further confirmation of their results, they often attempt to duplicate the results using diverse means. To the extent that they are successful in doing so, their results are said to be robust. This paper investigates the logic of such "robustness analysis" [RA]. The most important and challenging question an account of RA can answer is what sense of evidential diversity is involved in RAs. I argue that prevailing formal explications of such diversity are unsatisfactory. I propose a (...) unified, explanatory account of diversity in RAs. The resulting account is, I argue, truer to actual cases of RA in science; moreover, this account affords us a helpful, new foothold on the logic undergirding RAs. (shrink)

This article compares causal and constitutive explanation. While scientific inquiry usually addresses both causal and constitutive questions, making the distinction is crucial for a detailed understanding of scientific questions and their interrelations. These explanations have different kinds of explananda and they track different sorts of dependencies. Constitutive explanations do not address events or behaviors, but causal capacities. While there are some interesting relations between building and causal manipulation, causation and constitution are not to be confused. Constitution is a synchronous and (...) asymmetric relation between relata that cannot be conceived as independent existences. However, despite their metaphysical differences, the same key ideas about explanation largely apply to both. Causal and constitutive explanations face similar challenges (such as the problems of relevance and explanatory regress) and both are in the business of mapping networks of counterfactual dependence—i.e. mechanisms—although the relevant counterfactuals are of a different sort. In the final section the issue of developmental explanation is discussed. It is argued that developmental explanations deserve their own place in taxonomy of explanations, although ultimately developmental dependencies can be analyzed as combinations of causal and constitutive dependencies. Hence, causal and constitutive explanation are distinct, but not always completely separate forms of explanation. (shrink)

What features will something have if it counts as an explanation? And will something count as an explanation if it has those features? In the second half of the 20th century, philosophers of science set for themselves the task of answering such questions, just as a priori conceptual analysis was generally falling out of favor. And as it did, most philosophers of science just moved on to more manageable questions about the varieties of explanation and discipline-specific scientific explanation. Often, such (...) shifts are sound strategies for problem-solving. But leaving fallow certain basic conceptual issues can also result in foundational debates. (shrink)

This essay explores the connection between representation and explanation in the sciences. I suggest that scientific representation schemes be viewed as pragmatic tools for acquiring the sort of articulated awareness that is the hallmark of nontrivial knowledge. Crystal field theory in chemistry illustrates this perspective. Certain representations achieve the status of being paradigmatically explanatory, thereby shaping models of intelligibility. In turn, these explanatory preferences serve largely to define and differentiate disciplinary communities by implicitly endorsing particular epistemic aims and values. In (...) this way, the pragmatic nature of explanatory discourse effectively grants its intellectual utility. (shrink)

Systems medicine is a promising new paradigm for discovering associations, causal relationships and mechanisms in medicine. But it faces some tough challenges that arise from the use of big data: in particular, the problem of how to integrate evidence and the problem of how to structure the development of models. I argue that objective Bayesian models offer one way of tackling the evidence integration problem. I also offer a general methodology for structuring the development of models, within which the objective (...) Bayesian approach fits rather naturally. (shrink)

The mechanistic and causal accounts of explanation are often conflated to yield a ‘causal-mechanical’ account. This paper prizes them apart and asks: if the mechanistic account is correct, how can causal explanations be explanatory? The answer to this question varies according to how causality itself is understood. It is argued that difference-making, mechanistic, dualist and inferentialist accounts of causality all struggle to yield explanatory causal explanations, but that an epistemic account of causality is more promising in this regard.

This paper addresses questions about how the levels of causality (generic and single-case causality) are related. One question is epistemological: can relationships at one level be evidence for relationships at the other level? We present three kinds of answer to this question, categorised according to whether inference is top-down, bottom-up, or the levels are independent. A second question is metaphysical: can relationships at one level be reduced to relationships at the other level? We present three kinds of answer to this (...) second question, categorised according to whether single-case relations are reduced to generic, generic relations are reduced to single-case, or the levels are independent. We then explore causal inference in autopsy. This is an interesting case study, we argue, because it refutes all three epistemologies and all three metaphysics. We close by sketching an account of causality that survives autopsy—the epistemic theory. (shrink)

According to Michael Friedman’s theory of explanation, a law X explains laws Y1, Y2, …, Yn precisely when X unifies the Y’s, where unification is understood in terms of reducing the number of independently acceptable laws. Philip Kitcher criticized Friedman’s theory but did not analyze the concept of independent acceptability. Here we show that Kitcher’s objection can be met by modifying an element in Friedman’s account. In addition, we argue that there are serious objections to the use that Friedman makes (...) of the concept of independent acceptability. (shrink)

We suggest a rigorous theory of how objective single-case transition probabilities fit into our world. The theory combines indeterminism and relativity in the “branching space–times” pattern, and relies on the existing theory of causae causantes (originating causes). Its fundamental suggestion is that (at least in simple cases) the probabilities of all transitions can be computed from the basic probabilities attributed individually to their originating causes. The theory explains when and how one can reasonably infer from the probabilities of one “chance (...) set-up” to the probabilities of another such set-up that is located far away. (shrink)

I offer an explanation of why inertial and gravitational mass are equal in Newtonian gravitation. I then argue that this is an example of a kind of explanation that is not captured by standard philosophical accounts of scientific explanation. Moreover, this form of explanation is particularly important, at least in physics, because demands for this kind of explanation are used to motivate and shape research into the next generation of physical theories. I suggest that explanations of the sort I describe (...) reveal something important about one way in which physical theories may be related diachronically. (shrink)

I argue that the best interpretation of the general theory of relativity has need of a causal entity, and causal structure that is not reducible to light cone structure. I suggest that this causal interpretation of GTR helps defeat a key premise in one of the most popular arguments for causal reductionism, viz., the argument from physics.

Many philosophers now regard causal approaches to explanation as highly promising, even in physics. This is due in large part to James Woodward's influential argument that a wide variety of scientific explanations are causal, based on his interventionist approach to causation. This article argues that some derivations describing causal relations and satisfying Woodward's criteria for causal explanation fail to be explanatory. Further, causal relations are unnecessary for a range of explanations, widespread in physics, involving highly idealized models. These constitute significant (...) limitations on the scope of causal explanation. We have good reason to doubt that causal explanation is as widespread or important in physics as Woodward and other proponents maintain. (shrink)

In evolutionary biology changes in population structure are explained by citing trait fitness distribution. I distinguish three interpretations of fitness explanations—the Two‐Factor Model, the Single‐Factor Model, and the Statistical Interpretation—and argue for the last of these. These interpretations differ in their degrees of causal commitment. The first two hold that trait fitness distribution causes population change. Trait fitness explanations, according to these interpretations, are causal explanations. The last maintains that trait fitness distribution correlates with population change but does not cause (...) it. My defense of the Statistical Interpretation relies on a distinctive feature of causation. Causes conform to the Sure Thing Principle. Trait fitness distributions, I argue, do not. *Received July 2009; revised October 2009. †To contact the author, please write to: Department of Philosophy/Institute for the History, Philosophy of Science and Technology, University of Toronto, Victoria College, 91 Charles Street West, Toronto, ON M5S 1K7, Canada; e‐mail: [email protected]. (shrink)

In this paper, I outline two strands of evidence for the conclusion that the dynamical approach to cognitive science both seeks and provides covering law explanations. Two of the most successful dynamical models—Kelso’s model of rhythmic finger movement and Thelen et al.’s model of infant perseverative reaching—can be seen to provide explanations which conform to the famous explanatory scheme first put forward by Hempel and Oppenheim. In addition, many prominent advocates of the dynamical approach also express the provision of this (...) kind of explanation as a goal of dynamical cognitive science. I conclude by briefly outlining two consequences. First, dynamical cognitive science’s explanatory style may strengthen its links to the so-called “situated” approach to cognition, but, secondly, it may also undermine the widespread intuition that dynamics is related to emergentism in the philosophy of mind. (shrink)

Optimality models are widely used in different parts of biology. Two important questions that have been asked about such models are: are they explanatory and, if so, what type of explanations do they offer? My concern in this paper is with the approach of Rice (2012, 2015) and Irvine (2015), who claim that these models provide non-causal explanations. I argue that there are serious problems with this approach and with the accounts of explanation it is intended to justify. The idea (...) behind this undertaking is to draw attention to an important issue associated with the recent pluralist stance on explanation: the rampant proliferation of theories of explanation. This proliferation supports a pluralist perspective on explanation, and pluralism encourages such a proliferation. But, if we are not careful about how we arrive at and how we justify new accounts of explanation — i.e., if we do not try to avoid the sort of problems discussed in this paper — we may end up trivializing the concept of explanation. (shrink)

Can mathematics contribute to our understanding of physical phenomena? One way to try to answer this question is by getting involved in the recent philosophical dispute about the existence of mathematical explanations of physical phenomena. If there is such a thing, given the relation between explanation and understanding, we can say that there is an affirmative answer to our question. But what if we do not agree that mathematics can play an explanatory role in science? Can we still consider that (...) the above question can have an affirmative answer? My main aim here is to give an account that takes mathematics, in some of the cases discussed in the literature, as contributing to our understanding of physical phenomena despite not being explanatory. (shrink)

The principle that causes always render their effects more likely is fundamental to the enterprise of reducing facts of causation to facts about (objective) chances. This reductionist enterprise faces famous difficulties in accommodating common-sense intuitions about causal processes, if it insists on cashing out causal processes in terms of streams of events in which every event that belongs to the stream is a cause of the adjoining event downstream of it. I shall propose modifications to this way of cashing out (...) causal processes, still well within the reductionist faith. These modifications will allow the reductionist to handle processes successfully, on the assumption that the reductionist proposal is itself otherwise satisfactory. I shall then argue that the reductionist enterprise lies squarely behind the Theory of Relativity, and so has all the confirmatory weight of Relativity behind it. However this is not all good news for reductionists. For throughout I shall simply assume that the reductionist proposal, to the effect that causes are just chance-raisers, is correct. And I shall sidestep problems with that proposal as such. And so I shall show that, if in the end we find the reductionist proposal unsatisfactory, it cannot be on grounds of its treatment of causal processes as such. Thus, while I shall argue that causal processes pose no extra trouble for reductionists, I shall be making a case that all the action between reductionists and their opponents should be focused upon the proposal to reduce the two-term causal relation itself to relations amongst probabilities. (shrink)

A biochemical pathway is a sequence of chemical reactions in a biological organism. Such pathways specify mechanisms that explain how cells carry out their major functions by means of molecules and reactions that produce regular changes. Many diseases can be explained by defects in pathways, and new treatments often involve finding drugs that correct those defects. This paper presents explanation schemas and treatment strategies that characterize how thinking about pathways contributes to biomedical discovery. It discusses the significance of pathways for (...) understanding the nature of diseases, explanations, and theories. (shrink)

Why do people get sick? I argue that a disease explanation is best thought of as causal network instantiation, where a causal network describes the interrelations among multiple factors, and instantiation consists of observational or hypothetical assignment of factors to the patient whose disease is being explained. This paper first discusses inference from correlation to causation, integrating recent psychological discussions of causal reasoning with epidemiological approaches to understanding disease causation, particularly concerning ulcers and lung cancer. It then shows how causal (...) mechanisms represented by causal networks can contribute to reasoning involving correlation and causation. The understanding of causation and causal mechanisms provides the basis for a presentation of the causal network instantiation model of medical explanation. (shrink)

Social sciences face a well-known problem, which is an instance of a general problem faced as well by psychological and biological sciences: the problem of establishing their legitimate existence alongside physics. This, as will become clear, is a problem in metaphysics. I will show how a new account of structural explanations, put forward by Frank Jackson and Philip Pettit, which is designed to solve this metaphysical problem with social sciences in mind, fails to treat the problem in any importantly new (...) way. Then I will propose a more modest approach, and show how it does not deserve the criticism directed at a prototype by Jackson and Pettit. (shrink)

In this paper we argue that dissociative identity disorder (DID) is best interpreted as a causal model of a (possible) post-traumatic psychological process, as a mechanical model of an abnormal psychological condition. From this perspective we examine and criticize the evidential status of DID, and we demonstrate that there is really no good reason to believe that anyone has ever suffered from DID so understood. This is so because the proponents of DID violate basic methodological principles of good causal modeling. (...) When every ounce of your concentration is fixed upon blasting a winged pig out of the sky, you do not question its species' ontological status. James Morrow, City of Truth (1990). (shrink)

This article suggests a revision of the theory of causal nets. In section 1 we introduce an axiomatization of TCN based on a realistic understanding. It is shown that the causal Markov condition entails three independent principles. In section 2 we analyze indeterministic decay as the major counterexample to one of these principles: screening off by common causes. We call SCC-violating common causes interactive causes. In section 3 we develop a revised version of TCN, called TCN*, which accounts for interactive (...) causes. It is shown that there are interactive causal models that admit of no faithful noninteractive reconstruction. (shrink)

An important distinction is that between selective abductions, which select an optimal candidate from given multitude of possible explanations, and creative abductions, which introduce new theoretical concepts and models. The article focuses on creative abductions, which are essential for scientific progress, although they are rarely discussed in the literature. Scientifically, fruitful creative abductions are demarcated from purely speculative abductions by means of three virtues which are possessed by the former but not by the latter: (i) providing unification, (ii) detecting common (...) causes and (iii) generating novel predictions by means of which they can be independently tested. Based on historical examples it is demonstrated that common cause abduction from correlated dispositions is the fundamental abductive operation by which new theoretical concepts and models are scientifically generated. Statistical factor analysis can be regarded as a statistical generalization of common cause abduction. (shrink)

Two key ideas of scientific explanation−explanation as causal information and explanation as unification-have frequently been set into mutual opposition. This paper proposes a “dialectical solution” to this conflict, by arguing that causal explanations are preferable to non-causal ones, because they lead to a higherdegree of unification at the level of explaining statistical regularities. The core axioms of the theory of causal nets (TC) are justified because they offer the best if not the only unifying explanation of two statistical phenomena: screening (...) off and linking up. Alternative explanations of the two phenomena are discussed and it isshown why they don’t work. It is demonstrated that although the core axioms of TC are empirically vacuous, extended versions of TC have empirical content by means of which they can generate independently testable predictions.Con frecuencia se han planteado como contrapuestas dos ideas clave en la explicacion cientifica (explicacion como informacion causal y explicacion como unificacion). El presente articulo propone una “solucion dialectica” argumentando que las explicaciones causales son preferibles a las no-causales porque aquellas comportan un mayor grado de unificacion en la explicacion de regularidades estadisticas. Los axiomas centrales de la teoria de redes causales (TC) estan justificados porque ofrecen la mejor, si no la unica, explicacion unificada de dos fenomenos estadisticos: neutralizacion (screening off) y vinculacion (linking up). Se discuten las explicaciones alternativas de estos dos fenomenos y se razona por que no funcionan. Se demuestra ademas que aunque los axiomas centrales de TC son empiricamente vacuos, las versiones extendidas de TC tienen un contenido empirico gracias al cual pueden generar predicciones independientemente contrastables. (shrink)

The aim of this essay is to introduce philosophers of science to some recent philosophical discussions of the nature and origin of the direction of time. The essay is organized around books by Hans Reichenbach, Paul Horwich, and Huw Price. I outline their major arguments and treat certain critical points in detail. I speculate at the end about the ways in which the subject may continue to develop and in which it may connect with other areas of philosophy.

In this paper, I put forward a benchmark account of emergence in terms of non-explainability and explicate the relationship that exists between its synchronic and diachronic declinations. I develop an argument whose conclusion is that emergence is essentially a “two-faceted” notion, i.e. it always encapsulates both synchronic and diachronic dimensions. I then compare this account with alternative recent accounts of emergence that define the concept through the notion of unpredictability or topological non-equivalence.

The paper addresses the question of how different types of evidence ought to inform public health policy. By analysing case studies on obesity, the paper draws lessons about the different roles that different types of evidence play in setting up public health policies. More specifically, it is argued that evidence of difference-making supports considerations about ‘what works for whom in what circumstances’, and that evidence of mechanisms provides information about the ‘causal pathways’ to intervene upon.

The aim of this paper is to elaborate a notion of explanation which is applicable to stochastic processes such as quantum processes. The model-theoretic approach was adopted in order to delimit appropriate classes, by defining set-theoretical predicates, of different kinds of physical transformations that quantum systems suffer, either of transitions or of transmutations, by interaction or in a spontaneous manner. To explain a singular quantum process consists in showing that it is feasible to model it as an indeterministic process of (...) certain specified kind. (shrink)

In the world of philosophy of science, the dominant theory of confirmation is Bayesian. In the wider philosophical world, the idea of inference to the best explanation exerts a considerable influence. Here we place the two worlds in collision, using Bayesian confirmation theory to argue that explanatoriness is evidentially irrelevant.

The goal of this paper is to develop a counterfactual theory of explanation. The CTE provides a monist framework for causal and non-causal explanations, according to which both causal and non-causal explanations are explanatory by virtue of revealing counterfactual dependencies between the explanandum and the explanans. I argue that the CTE is applicable to two paradigmatic examples of non-causal explanations: Euler’s explanation and renormalization group explanations of universality.

In this paper, I aim to provide access to the current debate on non-causal explanations in philosophy of science. I will first present examples of non-causal explanations in the sciences. Then, I will outline three alternative approaches to non-causal explanations – that is, causal reductionism, pluralism, and monism – and, corresponding to these three approaches, different strategies for distinguishing between causal and non-causal explanation. Finally, I will raise questions for future research on non-causal explanations.

If $\mathcal{A}$ (V) is a net of local von Neumann algebras satisfying standard axioms of algebraic relativistic quantum field theory and V 1 and V 2 are spacelike separated spacetime regions, then the system ( $\mathcal{A}$ (V 1 ), $\mathcal{A}$ (V 2 ), φ) is said to satisfy the Weak Reichenbach's Common Cause Principle iff for every pair of projections A∈ $\mathcal{A}$ (V 1 ), B∈ $\mathcal{A}$ (V 2 ) correlated in the normal state φ there exists a projection C (...) belonging to a von Neumann algebra associated with a spacetime region V contained in the union of the backward light cones of V 1 and V 2 and disjoint from both V 1 and V 2 , a projection having the properties of a Reichenbachian common cause of the correlation between A and B. It is shown that if the net has the local primitive causality property then every local system ( $\mathcal{A}$ (V 1 ), $\mathcal{A}$ (V 2 ), φ) with a locally normal and locally faithful state φ and suitable bounded V 1 and V 2 satisfies the Weak Reichenbach's Common Cause Principle. (shrink)